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Real-Time Weapon Detection Using AI and IoT: A Case Study
技术
- 分析与建模 - 机器学习
- 网络安全和隐私 - 入侵检测
适用行业
- 教育
- 国家安全与国防
适用功能
- 产品研发
用例
- 计算机视觉
- 篡改检测
服务
- 云规划/设计/实施服务
- 系统集成
挑战
客户希望在四个月内将其计算机视觉云平台迁移到亚马逊云。需要进行迁移,以便该平台能够执行高度可扩展的实时武器检测,以识别高安全环境中的枪支和嫌疑人。他们还希望开发一种武器检测解决方案,可以与 AWS 云中的应用程序集成,以便能够快速有效地阻止、检测和防御射手。
关于客户
该客户是世界知名的自主系统先驱,旨在通过人工智能和机器学习支持的实时人类行为识别和武器检测技术,为重要企业、社区和学校提供安全保障。他们正在致力于众多政府和大型商业项目,并继续发展其武器检测解决方案,以应对未来的安全挑战。
解决方案
Provectus 和客户的工程团队联手在 AWS 上设计了可持续的解决方案,以满足实时处理多个安全摄像头源的需求。该解决方案涉及在 Amazon SageMaker 上部署专有的 ML 模型、应用 DevOps 最佳实践、推出视频解码引擎、更换客户的新 UI 以及将 IoT 警报系统与 Alexa 通知集成。 Provectus 还实现了带有交互式时间线的自定义 UI,可轻松进行相机和用户管理、自定义垃圾箱、收藏夹标记系统以及通知和警报。
运营影响
数量效益
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